Analysis Of Irregularities In Shunting Operations Of Coal Mining Enterprises Based On Correlation Rules

As a pillar industry in the national economy,the coal mining industry is closely related to China’s economic development.Coal transportation is an important part of coal mining enterprises,and shunting operations occupy an extremely important position in the railway transportation of coal mining enterprises.Due to the influence of many factors such as the changeable location of the shunting operation,the irregularity of the working object,the large difference in the skill level of the personnel,the weather environment and other factors,the safety management of the shunting operation is more difficult.The traditional shunting operation safety management method is mainly passive management after the occurrence of illegal operations,and does not pay attention to active prevention in advance.From the perspective of advanced safety protection for the shunting operation of coal mining enterprises,this paper mines 1047 illegal operation records of a coal mining enterprise in the past five years,finds some potential laws,and puts forward targeted safety management suggestions based on this information,the main work is as follows:(1)On the basis of the analysis of the railway transportation shunting operation of coal mining enterprises,combined with the characteristics of coal mining enterprises themselves,it is found that the shunting operation of coal mining enterprises has the characteristics of multi-faceted and varied conditions,and five factors affecting the shunting operation are proposed,and on this basis,a theoretical model of the relationship between the results of violations and the influencing factors is established,and the use of FP-growth association rule algorithm is determined the mines data recorded in violation of the law.(2)Introduces an objective measure of "lift" on the "support-confidence" screening framework based on the association rule,set the lift threshold to greater than 1,set the minimum support degree to 10,and introduce an adaptive threshold algorithm to determine the confidence threshold of different influencing factors and use it The Python language programmed the data mining process and eventually generated 3163 correlation rules.(3)The correlation rules are classified and analyzed according to different influencing factors,and the correlation rules are interpreted by the method of knowledge representation,revealing the potential laws in the massive violation records;according to the data mining results,the safety management suggestions are put forward in a targeted manner to achieve the active prevention of the enterprise’s safety management of daily shunting operations.